Feasibility of Use of Fitbit, Brief DSMES, and Targeted Text Messaging in Sedentary Adults with Type 2 Diabetes in Primary Care Settings (FIT T2D)

Keywords

Type 2 diabetes, artificial intelligence, diabetes technology, Fitbit, physical activity, education, remote patient monitoring

Types of Research

Clinical research

Primary Objective

To determine if providing a Fitbit plus artificial intelligence (AI)-tailored and delivered diabetes self-management education and support (DSMES) with tailored text messages can improve clinical outcomes (e.g. a1c, BMI) in primary care patients with type 2 diabetes.

Description

Participants with type 2 diabetes who do not meet American Diabetes Association (ADA) recommendations for physical activity will participate in this 12-week trial. All participants will receive a FitBit device to track physical activity levels and will be instructed to interact with an AI Chatbot that will provide recommendations and ideas for increasing or maintaining physical activity levels. FitBit data will be shared and reviewed with the participant and their doctor. Clinical and psychosocial outcomes will be collected pre and post participation.

Eligibility Criteria

Inclusion criteria:

Diagnosed with type 2 diabetes
Age ≥18 years and ≤ 80 years
Does not meet ADA guidelines for physical activity (< 150 minutes of aerobic exercise per week defined as any activity where the participant can talk but not sing)
Has a smartphone compatible with a Fitbit

Exclusion criteria:

Completing more than 60 minutes of moderate to vigorous activity per week defined as activity where you cannot sing (moderate) or can’t say more than a few words without gasping for breath (vigorous)
Any medical condition which, in the opinion of the investigator, would put the participant at an unacceptable safety risk, such as untreated malignancy, unstable cardiac disease, unstable or end-stage renal disease, and/or eating disorders.
Current or known history of coronary artery disease that is not stable with medical management, including unstable angina, or angina that prevents moderate exercise despite medical management, or a history of myocardial infarction, percutaneous coronary intervention, or coronary artery bypass grafting within the previous 12-months
Any planned surgery during the study which could be considered major in the opinion of the investigator
Blood disorder or dyscrasia within 3 months before screening, or the use of hydroxyurea, which, in the investigator’s opinion, could interfere with the determination of HbA1c
Has taken oral or injectable steroids within the past 8 weeks or plans to take oral or injectable steroids during the study, as they may interfere with the determination of HbA1c.
Planning to move from Colorado within 3 months
Current Pregnancy or planning on pregnancy in the next 3 months
Unable to safely comply with study procedures and reporting requirements (e.g. impairment of vision that impacts ability to see FitBit, impaired memory)
Unable to speak English as this is a small feasibility study that does not have the resources to adapt the intervention for Spanish
Current participation in another diabetes-related clinical trial

Significance

With the increasing prevalence of type 2 diabetes in primary care settings, interventions are needed to assist patients in reaching their activity goals and improving their health outcomes. Incorporating technology-assisted interventions, such as an AI Chatbot combined with FitBit technology, may improve health outcomes for sedentary patients with type 2 diabetes.

Impact

This results of this study may influence the future use and integration of AI-delivered DSMES and wearable technologies in primary care practices. Participation may also improve patient lives by increasing physical activity and improving social, mental, emotional, and/or physical well-being.

Lessons Learned

Coming soon.

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